A Modified Bi-Directional Evolutionary Structural Optimization Procedure with Variable Evolutionary Volume Ratio Applied to Multi-Objective Topology Optimization Problem

Natural frequency and dynamic stiffness under transient loading are two key performances for structural design related to automotive,aviation and construction industries.This article aims to tackle the multi-objective topological optimization problem considering dynamic stiffness and natural frequency using modified version of bi-directional evolutionary structural optimization(BESO).The conventional BESO is provided with constant evolutionary volume ratio(EVR),whereas low EVR greatly retards the optimization process and high EVR improperly removes the efficient elements.To address the issue,the modified BESO with variable EVR is introduced.To compromise the natural frequency and the dynamic stiffness,a weighting scheme of sensitivity numbers is employed to form the Pareto solution space.Several numerical examples demonstrate that the optimal solutions obtained from the modified BESO method have good agreement with those from the classic BESO method.Most importantly,the dynamic removal strategy with the variable EVR sharply springs up the optimization process.Therefore,it is concluded that the modified BESO method with variable EVR can solve structural design problems using multi-objective optimization.

Stress Relaxation and Sensitivity Weight for Bi-Directional Evolutionary Structural Optimization to Improve the Computational Efficiency and Stabilization on Stress-Based Topology Optimization

Stress-based topology optimization is one of the most concerns of structural optimization and receives much attention in a wide range of engineering designs.To solve the inherent issues of stress-based topology optimization,many schemes are added to the conventional bi-directional evolutionary structural optimization(BESO)method in the previous studies.However,these schemes degrade the generality of BESO and increase the computational cost.This study proposes an improved topology optimization method for the continuum structures considering stress minimization in the framework of the conventional BESO method.A global stress measure constructed by p-norm function is treated as the objective function.To stabilize the optimization process,both qp-relaxation and sensitivity weight scheme are introduced.Design variables are updated by the conventional BESO method.Several 2D and 3D examples are used to demonstrate the validity of the proposed method.The results show that the optimization process can be stabilized by qp-relaxation.The value of q and p are crucial to reasonable solutions.The proposed sensitivity weight scheme further stabilizes the optimization process and evenly distributes the stress field.The computational efficiency of the proposed method is higher than the previous methods because it keeps the generality of BESO and does not need additional schemes.

A Smooth Bidirectional Evolutionary Structural Optimization of Vibrational Structures for Natural Frequency and Dynamic Compliance

A smooth bidirectional evolutionary structural optimization(SBESO),as a bidirectional version of SESO is proposed to solve the topological optimization of vibrating continuum structures for natural frequencies and dynamic compliance under the transient load.A weighted function is introduced to regulate the mass and stiffness matrix of an element,which has the inefficient element gradually removed from the design domain as if it were undergoing damage.Aiming at maximizing the natural frequency of a structure,the frequency optimization formulation is proposed using the SBESO technique.The effects of various weight functions including constant,linear and sine functions on structural optimization are compared.With the equivalent static load(ESL)method,the dynamic stiffness optimization of a structure is formulated by the SBESO technique.Numerical examples show that compared with the classic BESO method,the SBESO method can efficiently suppress the excessive element deletion by adjusting the element deletion rate and weight function.It is also found that the proposed SBESO technique can obtain an efficient configuration and smooth boundary and demonstrate the advantages over the classic BESO technique.

Structural Topology Optimization by Combining BESO with Reinforcement Learning

In this paper,a new algorithm combining the features of bi-direction evolutionary structural optimization(BESO)and reinforcement learning(RL)is proposed for continuum structural topology optimization(STO).In contrast to conventional approaches which only generate a certain quasi-optimal solution,the goal of the combined method is to provide more quasi-optimal solutions for designers such as the idea of generative design.Two key components were adopted.First,besides sensitivity,value function updated by Monte-Carlo reinforcement learning was utilized to measure the importance of each element,which made the solving process convergent and closer to the optimum.Second,ε-greedy policy added a random perturbation to the main search direction so as to extend the search ability.Finally,the quality and diversity of solutions could be guaranteed by controlling the value of compliance as well as Intersection-over-Union(IoU).Results of several 2D and 3D compliance minimization problems,including a geometrically nonlinear case,show that the combined method is capable of generating a group of good and different solutions that satisfy various possible requirements in engineering design within acceptable computation cost.

Structural Optimization of Hatch Cover Based on Bi-directional Evolutionary Structure Optimization and Surrogate Model Method

Weight reduction has attracted much attention among ship designers and ship owners.In the present work,based on an improved bi-directional evolutionary structural optimization(BESO) method and surrogate model method,we propose a hybrid optimization method for the structural design optimization of beam-plate structures,which covers three optimization levels:dimension optimization,topology optimization and section optimization.The objective of the proposed optimization method is to minimize the weight of design object under a group of constraints.The kernel optimization procedure(KOP) uses BESO to obtain the optimal topology from a ground structure.To deal with beam-plate structures,the traditional BESO method is improved by using cubic box as the unit cell instead of solid unit to construct periodic lattice structure.In the first optimization level,a series of ground structures are generated based on different dimensional parameter combinations,the KOP is performed to all the ground structures,the response surface model of optimal objective values and dimension parameters is created,and then the optimal dimension parameters can be obtained.In the second optimization level,the optimal topology is obtained by using the KOP according to the optimal dimension parameters.In the third optimization level,response surface method(RSM) is used to determine the section parameters.The proposed method is applied to a hatch cover structure design.The locations and shapes of all the structural members are determined from an oversized ground structure.The results show that the proposed method leads to a greater weight saving,compared with the original design and genetic algorithm(GA) based optimization results.

Topology Optimization in Damping Structure Based on ESO

The damping material optimal placement for the structure with damping layer is studied based on evolutionary structural optimization (ESO) to maximize modal loss factors. A mathematical model is constructed with the objective function defined as the maximum of modal loss factors of the structure and design constraints function defined as volume fraction of damping material. The optimal placement is found. Several examples are presented for verification. The results demonstrate that the method based on ESO is effective in solving the topology optimization of the structure with unconstrained damping layer and constrained damping layer. This optimization method suits for free and constrained damping structures.

基于BESO算法的大型海洋垂直轴风力机支撑结构优化

大型海洋垂直轴风力机的研究对发展海洋风能具有重要意义,研究大型垂直轴风力机的合理支撑结构形式对风力发电结构安全至关重要.基于变删除率的双向渐进结构优化(BESO)算法,对大型海洋垂直轴风力机进行支撑结构优化,并通过风力机的动力响应特性分析,验证结构优化方法的可靠性.结果表明:反比例型变删除率的BESO算法能有效改善优化迭代速率,适用于垂直轴风力机的支撑结构优化设计;相比于初始结构,拓扑出的新结构模型在风荷载作用下的风致动力响应显著降低.研究成果可用于垂直轴风力机支撑结构设计优化.

基于BESO方法的连续体结构动态特性多目标拓扑优化

为实现动态多目标下的拓扑优化结构设计,以结构动柔顺度最小化和固有频率最大化加权函数为目标,提出基于双向渐进结构优化方法(Bi-direction Evolutionary Structural Optimization, BESO)的连续体结构动态特性多目标拓扑优化方法。基于等效静载荷法(Equivalent Static Loads, ESL),将结构动刚度优化问题转化为多工步载荷作用下的线性静刚度优化问题,结合BESO方法实现结构多工况线性静态优化。分别归一化目标函数和灵敏度,避免不同性质目标函数及灵敏度的量级差异引起的数值奇异性。数值算例结果表明,结构体积约束、频率与动柔顺度综合目标均能渐进收敛于最优目标值,优化结构具有清晰的拓扑构型。随着柔顺度灵敏度、权重因子的减小,优化结构拓扑形式发生显著变化,其动刚度逐渐减小,而固有频率逐渐增加。所提出的频率-动刚度多目标拓扑优化方法能够提高结构动态特性,拓展了BESO方法对结构动力学拓扑优化问题的应用范围。

声子晶体能带结构仿真的CS-FEM方法及其在拓扑优化设计中的应用

针对声子晶体拓扑优化设计时能带结构和灵敏度计算效率低的缺陷,构造了一种Cell-based光滑有限元法模型(CS-FEM),并结合双向渐进结构优化法(BESO)实现了声子晶体的带隙最大化设计。基于四边形单元构造光滑子域,将梯度光滑技术与Bloch定理结合,构建了声子晶体能带结构计算的CS-FEM数值模型,并将其用于正问题的仿真模拟。在渐进优化准则下,通过BESO算法完成了声子晶体的优化设计。数值算例表明:CS-FEM能够适当软化离散系统的刚度,提供更加准确、高效的能带结构仿真结果;基于CS-FEM进行正问题的计算,在优化设计中得到了最优的拓扑构型,并有效地提高了优化效率,对于实现声子晶体的高效设计具有重要的参考价值。

基于双向渐进结构优化算法的预制拼装箱梁剪力键设计研究

为研究单项和多项荷载组合作用下节段预制拼装箱梁接缝处剪力键受力状况,以郑州南四环全预制装配高架桥为背景,采用Abaqus软件和双向渐进结构优化(BESO)算法,建立典型箱梁节段分析模型,研究剪力键在单位轴力、剪力、扭矩、弯矩和不同荷载组合作用下的布置规律。结果表明:轴力作用时剪力键应布置于顶板;剪力作用时剪力键应布置于腹板和底板;扭矩作用时剪力键应布置在顶板、腹板交接处和腹板外侧;横桥向弯矩作用时剪力键应布置于顶板、腹板下侧和底板;竖向弯矩作用时,剪力键应布置于顶板翼缘。轴剪组合作用下,当剪力占比小于50%时,轴力对剪力键布置起控制作用;当剪力占比达95.24%时,剪力对剪力键布置起控制作用。弯剪组合作用下,当剪力占比超过4.76%时,剪力对剪力键布置起控制作用;当剪力占比小于0.50%时,横桥向弯矩对剪力键布置起控制作用。扭剪组合作用下,当剪力占比超过0.10%时,剪力对剪力键布置起控制作用。预制拼装箱梁剪力键布置受荷载类型及荷载组合影响显著,应考虑不同位置剪力键的实际受力状况进行设计。

Layout optimization of steel reinforcement in concrete structure using a truss-continuum model

Owing to advancement in advanced manufacturing technology,the reinforcement design of concrete structures has become an important topic in structural engineering.Based on bi-directional evolutionary structural optimization(BESO),a new approach is developed in this study to optimize the reinforcement layout in steel-reinforced concrete(SRC)structures.This approach combines a minimum compliance objective function with a hybrid trusscontinuum model.Furthermore,a modified bi-directional evolutionary structural optimization(M-BESO)method is proposed to control the level of tensile stress in concrete.To fully utilize the tensile strength of steel and the compressive strength of concrete,the optimization sensitivity of steel in a concrete–steel composite is integrated with the average normal stress of a neighboring concrete.To demonstrate the effectiveness of the proposed procedures,reinforcement layout optimizations of a simply supported beam,a corbel,and a wall with a window are conducted.Clear steel trajectories of SRC structures can be obtained using both methods.The area of critical tensile stress in concrete yielded by the M-BESO is more than 40%lower than that yielded by the uniform design and BESO.Hence,the M-BESO facilitates a fully digital workflow that can be extremely effective for improving the design of steel reinforcements in concrete structures.

基于BESO算法的邮轮结构开孔拓扑优化

以大型邮轮舱段中的船底旁桁材结构为研究对象,采用结构优化算法,对大型豪华邮轮船底桁材结构进行开孔,并对其结构加以优化。结合多工况的船体结构优化的BESO算法,在特定的设计域内进行结构拓扑优化。在此基础上,分析了10种工况下优化开孔前后最大应力、平均应力和体积的变化,并对孔型结构进行了优化,以分析新开孔的力学性能。优化结果显示,在满足船体刚度的条件下,优化后,新式开孔的最大应力比优化前提高了44.26%。开孔后的面积比优化后减少51%,达到了轻量化的目的。研究结果可以用于指导船体建造。

复合材料/结构两尺度动力学拓扑优化设计

基于均匀化理论,建立以结构第一阶固有频率最大为目标的宏/微观结构构型与材料分布的两尺度动力学拓扑优化模型,推导目标函数和约束函数对宏/微观设计变量的灵敏度,研究两尺度动力学拓扑优化方法。另外,采用一个修正固体各向同性材料惩罚(SIMP)模型避免局部模态现象。相关数值算例说明,该方法可以有效实现结构基频最大化的材料/结构两尺度动力学拓扑优化设计。此外,通过算例研究复合材料的弹性模量对优化结果的影响规律。

基于刚度与应力问题的多相材料双尺度拓扑优化研究

本文针对双尺度晶格结构的优化设计,在质量约束条件下,提出了一种将均匀化方法与快速非支配排序遗传算法(NSGA-Ⅱ)相结合的拓扑优化方法,并引入双向渐进(BESO)思想指导单元的增删.对于双尺度优化设计,利用均匀化理论实现了微观尺度与宏观尺度的耦合.为了解决工程应用中的多相材料布局以及结构刚度、应力双目标优化问题,引入带有加权因子的材料插值方案,利用改进的密度插值函数推导出带惩罚因子的灵敏度计算公式,利用全局p范数应力方案消除应力的局部行为.为了使多相微观结构具有较强的边界连通性,对微观单元进行基于密度的边界设计.最后,对经典的L型梁与二维支撑结构进行优化设计,分析了p范数应力参数对优化结果的影响.结果表明,所提出的算法可以有效地使双目标达到最优解的平衡状态.此外,通过与经典的均匀化算法以及相关领域研究的结果进行对比,证明了所提出算法在多相材料以及双目标优化问题中的优越性,为未来双尺度优化解决工程问题提供了一定的理论基础.

考虑质量约束的多相材料结构拓扑优化新方法

提出了一种将双向渐进法(BESO)与快速非支配排序遗传算法(NSGA-Ⅱ)相结合的拓扑优化方法,称为BESO-NSGA-Ⅱ方法.与传统双向渐进法的体积约束不同,本文算法以质量作为约束条件,并采用多相材料插值方案实现了多相材料的优化分布.通过大量的算例,证明了算法的稳定性和有效性.与传统双向渐进法相比,新算法在相同约束条件下能有效地提高结构刚度.同时,为了获得干净的拓扑,该算法提出了在交叉变异过程中使用的双惩罚算子来实现干净的拓扑结构.结果表明,该算法能较好地实现结构的轻量化设计.

COMPUTER PROGRAM FOR DIRECTED STRUCTURE TOPOLOGY OPTIMIZATION

To compensate for the imperfection of traditional bi-directional evolutionary structural optimization, material interpolation scheme and sensitivity filter functions are introduced. A suitable filter can overcome the checkerboard and mesh-dependency. And the historical information on accurate elemental sensitivity numbers are used to keep the objective function converging steadily. Apart from rational intervals of the relevant important parameters, the concept of distinguishing between active and non-active elements design is proposed, which can be widely used for improving the function and artistry of structures directly, especially for a one whose accurate size is not given. Furthermore, user-friendly software packages are developed to enhance its accessibility for practicing engineers and architects. And to reduce the time cost for large timeconsuming complex structure optimization, parallel computing is built-in in the MATLAB codes. The program is easy to use for engineers who may not be familiar with either FEA or structure optimization. And developers can make a deep research on the algorithm by changing the MATLAB codes. Several classical examples are given to show that the improved BESO method is superior for its handy and utility computer program software.

基于双尺度拓扑优化的多相材料结构设计方法

针对双尺度优化问题,研究小组提出了一种将双向渐进法(BESO)与快速非支配排序遗传算法(NSGA-Ⅱ)相结合的拓扑优化方法,称为BESO-NSGA-Ⅱ。通过基于能量的均匀化理论推导非均质材料的有效性质,并采用多相材料插值方案实现双尺度结构多相材料的拓扑优化。为了获得“干净”的拓扑,BESO-NSGA-Ⅱ算法提出了在交叉变异过程中使用双惩罚算子来实现“干净”的拓扑结构。通过算例并与经典BESO算法进行对比,验证了BESO-NSGA-Ⅱ算法的稳定性和有效性及其获得收敛解的能力,以期为后续的双尺度拓扑优化研究提供参考依据。

基于改进的双向渐进结构优化法的应力约束拓扑优化

工程结构设计时经常需要限制最大名义应力,以避免发生断裂或疲劳破坏,一个有效的策略是采用拓扑优化方法.常规的双向渐进结构优化法(bi-evolutionary structural optimization,BESO)不能有效求解应力约束拓扑优化问题,为此本文提出一种改进的双向渐进结构优化方法,处理体积和应力约束下的最小柔顺性问题.引入基于K-S函数的全局应力度量,以减小大量局部应力约束引起的计算代价.采用拉格朗日乘子法将应力约束函数引入到目标函数,然后由二分法确定合适的拉格朗日乘子的值使得应力约束得到满足.而且,详细推导了基于BESO方法的应力约束拓扑优化模型及其灵敏度列式,最后通过三个典型拓扑优化算例验证改进方法的有效性.为展示考虑应力约束的优点,将应力约束设计与传统的基于刚度的设计进行了比较.结果表明,改进的BESO方法优化迭代过程稳健,获得了边界灰度单元很少的清晰的拓扑构型,并实现了有效降低应力集中效应的设计.

以频率为目标的加筋平板结构优化设计研究

以加筋平板结构的多阶模态频率达到指定值为优化目标,探讨结构的优化设计方法。提出一种双向渐进结构拓扑优化法结合尺寸优化方法的结构频率优化设计的改进方法。该方法采用具有规则格栅骨架的加筋平板结构优化模型,以骨架中的梁为结构修改基本单位,以梁敏度计算为基础。实现以频率为目标函数、以体积为约束,并结合敏度再分配策略的结构优化设计。最后,运用尺寸优化方法对优化结果进行后续详细设计。经加筋平板结构频率优化设计算例证明,该方法能满足结构的多阶模态频率优化要求;同时优化结果不存在一般拓扑优化的不规则结构问题,抑制局部模态的产生,对飞机风洞颤振实验模型的设计具有借鉴意义。

基于柔性机构的机翼前缘变形多目标优化

全柔性机构用于自适应机翼具有实现其形状的连续平滑变形和轻量化等优点。文章根据机翼前缘在不同飞行状态下气动外形要求,以离散体结构拓扑优化为出发点,以目标形状与实际形状的边界曲线之差最小为优化目标,并考虑机构变形要求和刚性要求等问题,建立了多目标优化函数;采用遗传算法(GA)和双向渐进结构优化法(BESO)相结合,应用于Matlab与Ansys,通过二次优化,获得了稳定的最优解,不仅实现编程模块化,而且提高了优化效率。最后,对结果进行Ansys仿真分析和模型实验验证。结果表明:仿真结果和模型实验结果一致,该方法是可行的。